removed the NQ training split for less confusion
Browse files
NaturalQuestions/qrels/train.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:b76d5e65310096d76ad43d8f1a1a5ba6757a24ccaa84d1e080e0de4eb295c486
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size 431420
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NaturalQuestions/queries/train.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:9c51904723964016bfc958ea7907a0a29ca6b22b3bec2bde859d49b86102d223
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size 1132387
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README.md
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path: NaturalQuestions/nq-hard/*
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- config_name: NaturalQuestions-queries
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data_files:
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- split: train
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path: NaturalQuestions/queries/train.parquet
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- split: dev
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path: NaturalQuestions/queries/dev.parquet
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- split: test
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path: NaturalQuestions/queries/test.parquet
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- config_name: NaturalQuestions-qrels
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data_files:
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- split: train
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path: NaturalQuestions/qrels/train.parquet
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- split: dev
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path: NaturalQuestions/qrels/dev.parquet
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- split: test
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@@ -176,6 +172,8 @@ And additionally, NQ-hard, the hard subset of queries from Natural Questions is
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> Notes: for MS MARCO, its documents do not provide the gold paragraph segmentation and we only segment the document by keeping the judged passages (from the MS MARCO Passage Ranking task) standing out while leaving the rest parts surrounding these passages. These passages are marked by `is_candidate==true`.
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## Load the dataset
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### Loading the passages
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One can load the passages like this:
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path: NaturalQuestions/nq-hard/*
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- config_name: NaturalQuestions-queries
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data_files:
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- split: dev
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path: NaturalQuestions/queries/dev.parquet
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- split: test
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path: NaturalQuestions/queries/test.parquet
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- config_name: NaturalQuestions-qrels
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data_files:
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- split: dev
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path: NaturalQuestions/qrels/dev.parquet
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- split: test
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> Notes: for MS MARCO, its documents do not provide the gold paragraph segmentation and we only segment the document by keeping the judged passages (from the MS MARCO Passage Ranking task) standing out while leaving the rest parts surrounding these passages. These passages are marked by `is_candidate==true`.
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> For Natural Questions, the training split is not provided because the duplidate timestamps cannot be compatible with the queries/qrels/corpus format. Please refer to https://public.ukp.informatik.tu-darmstadt.de/kwang/dapr/data/NaturalQuestions/ for the training split.
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## Load the dataset
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### Loading the passages
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One can load the passages like this:
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